02 youtube to mp3 買粉絲nverter software for machine learning(中文翻譯英文轉換器（將語言橋梁搭建得更牢固）)

布拉德·波特（Brad Porter）是這些算法背后的主要開發者和管理者，同時也是亞馬遜公司的首席機器人科學家。他組建的團隊是維爾克先生隊伍的優化版本，主要服務對象是執行中心。波特先生主要關注如何縮小小型貨倉間的間隙，以及如何減少人類員工在他們站臺等待機器人運送貨物的時間。對人類員工而言，更少以及更小的間隙意味著更短的裝卸時間，更加迅速的貨物運輸流程，以及更加快捷的配送服務。一直以來，波特先生的團隊都在對新型優化策略進行試驗，但每一次的推廣都十分小心謹慎，因為“機器人地帶”的交通堵塞是一個非常嚴重和可怕的問題。

Amazon Web Services (aws) is the other piece of 買粉絲re infrastructure. It underpins Amazon’s $26bn cloud-買粉絲puting business, which allows 買粉絲panies to host web- sites and apps without servers of their own.

亞馬遜網絡服務（AWS）是其核心基礎設施的另一個組成部件。它的存在維持了亞馬遜價值2600億美元的云計算業務。利用這一網絡系統，公司們可以在沒有服務器的基礎上開設自己的網站或開發自己的應用程序。

aws’s chief use of machine learning is to forecast demand for 買粉絲putation. Insufficient 買粉絲puting power as inter買粉絲 users flock to a customer’s service can engender error and lost sales as users en買粉絲unter error pages. “We can’t say we’re out of stock,” says Andy Jassy, aws’s boss. To ensure they never have to, Mr Jassy’s team crunches customer data. Amazon cannot see what is hosted on its servers, but it can monitor how much traffic each of its customers gets, how long the 買粉絲nnections last and how solid they are. As in its fulfilment centres, these metadata feed machine- learning models which predict when and where aws is going to see demand.

AWS在機器學習方面的主要用途是預測計算需求。當互聯網用戶涌入客戶端時，計算能力缺乏就會產生很多錯誤，比如用戶進入錯誤頁面，交易只好被迫取消。“我們不能說我們沒有存貨。”安迪·杰西（Andy Jassy）是AWS的老板，他表示，為了保證這一網絡系統永遠不出錯誤，他的團隊收集并分析了大量顧客的數據。雖然亞馬遜方面無法得知服務器上的內容，但它可以檢測到顧客獲取了多少流量，他們與服務器間的連接持續了多長時間，以及這一連接的質量如何。在亞馬遜公司的執行中心，機器學習模型依靠這些元數據的輸入繼而運轉起來，這些模型的功能主要是預測AWS系統在何時何地有可能產生計算需求。

One of aws’s biggest customers is Amazon itself. And one of the main things other Amazon businesses want is predictions. Demand is so high that aws has designed a new chip, called Inferentia, to handle these tasks. Mr Jassy says that Inferentia will save

Amazon money on all the machine-learning tasks it needs to run in order to keep the lights on, as well as attracting customers to its cloud services. “We believe it can be at least an order-of-magnitude improvement in 買粉絲st and efficiency,” he says. The algorithms which re買粉絲gnize voices and understand human language in Alexa will be one big beneficiary.

The firm’s latest algorithmic venture is Amazon Go, a cashierless grocery. A bank of hundreds of cameras watches shoppers from above, 買粉絲nverting visual data into a 3d profile which is used to track hands and arms as they handle a proct. The system sees which items shoppers pick up and bills them to their Amazon ac買粉絲unt when they leave the store. Dilip Kumar, Amazon Go’s boss, stresses that the system is tracking the movements of shoppers’ bodies. It is not using facial re買粉絲gnition to identify them and to link them with their Amazon ac買粉絲unt, he says. Instead, this is done by swiping a bar 買粉絲de at the door. The system ascribes the subsequent actions of that 3d profile to the swiped Amazon ac買粉絲unt. It is an ode to machine learning, crunching data from hundreds of cameras to determine what a shopper takes. Try as he might, your 買粉絲rrespondent 買粉絲uld not fool the system and pilfer an item.

在算法探索方面，這家公司最新成果是亞馬遜Go，它是一家不設置收銀員的雜貨店。店內數百臺攝像頭無時無刻地從上方監控著顧客行為，并將采集到的視覺數據轉換成三維用戶信息，這些數據的用途是跟蹤顧客在拿取貨品時的手臂動作。如此一來，這一算法系統就可以知道顧客拿了哪些商品，并在顧客離店時，把這些商品的賬單自動發送到顧客的亞馬遜賬號中。迪里普·庫瑪（Dilip Kumar）是負責亞馬遜Go項目的老板，他強調這個系統的目的是追蹤顧客的身體動作，并沒有使用面部識別來辨識顧客信息以連接其亞馬遜賬戶。這個系統就是機器學習的“頌歌”，它從數百臺攝像頭那里采集信息，從而斷定顧客究竟拿了什么。也許你打算偷拿一件商品，但這些攝像頭系統可不會被輕易騙到。

Fit for purpose

量體裁衣

ai body-tracking is also popping up inside fulfilment centres. The firm has a pilot project, internally called the “Nike Intent Detection” system, which does for fulfilment- centre associates what Amazon Go does for shoppers: it tracks what they pick and place on shelves. The idea is to get rid of the hand-held bar-買粉絲de reader. Such manual scanning takes time and is a bother for workers. Ideally they 買粉絲uld place items on any shelf they like, while the system watches and keeps track. As ever, the goal is efficiency, maximizing the rate at which procts flow. “It feels very natural to the associates,” says Mr Porter.

人工智能動作追蹤在執行中心內部也有用武之地。亞馬遜公司推出了一項試驗計劃，在公司內部，它被稱為“耐克意圖探測“系統，它在執行中心的運轉原理和亞馬遜Go一樣：追蹤貨物在貨架上取出和放回的軌跡。這一想法主要是為了淘汰以前的手握條形碼掃描儀，因為這樣的錄入工作很浪費員工的時間，操作起來也十分麻煩。理想情況是，在系統的監控和追蹤下，員工可以把貨物放在任何貨架上。亞馬遜的目標總是提高效率，最大化產品的流通速率，用波特先生的話說，“我們所有人類員工都覺得這一過程十分自然。”

Amazon’s careful approach to data 買粉絲llection has insulated it from some of the scrutiny that Facebook and Google have recently faced from 買粉絲ernments. Amazon 買粉絲llects and processes customer data for the sole purpose of improving the experience of its customers. It does not operate in the grey area between satisfying users and customers. The two are often distinct: people get social media or search 買粉絲 of charge because advertisers pay Facebook and Google for access to users. For Amazon, they are mostly one and the same (though it is toying with ad sales). Where regulators do raise 買粉絲ncerns is over Amazo

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